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Mardiyyah/CeLLaTe-tapt-bioformer16l-tokenizer-original-baseline

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face
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CeLLaTe-tapt-bioformer16l-tokenizer-original-baseline

This model is a fine-tuned version of bioformers/bioformer-16l on the Mardiyyah/TAPT_CeLLaTe2.0 dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.2118
  • —Accuracy: 0.7444
  • —Perplexity: 3.3596

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 3e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 3407
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 64
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.06
  • —num_epochs: 100
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracyPerplexity
1.471.0151.27420.73513.5759
1.46452.0301.27520.73313.5796
1.4443.0451.25060.74103.4925
1.40364.0601.22670.74293.4099
1.37375.0751.20510.74533.3370
1.35846.0901.21330.74443.3645
1.34577.01051.18600.75003.2738
1.31468.01201.22540.74643.4055
1.30819.01351.22810.74223.4146
1.290610.01501.18610.74763.2744
1.264411.01651.21250.74603.3618
1.266512.01801.20330.74913.3310

Framework versions

  • —Transformers 4.48.2
  • —Pytorch 2.4.1+cu121
  • —Datasets 3.0.2
  • —Tokenizers 0.21.0